skills.rest
pollinations
pollinationsOFFICIAL
Explore all skills by this author →
Website𝕏@pollinations_aiGitHub

model-debugging

Diagnose model failures and identify affected users from Tinybird and Cloudflare logs.

4.9k|974|Updated Apr 15, 2021
Search Tags:#debugging#monitoring#logs#observability#cloudflare#model#tinybird
One-click install
npx skills add https://github.com/pollinations/pollinations --skill model-debugging
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-debugging
Source: https://github.com/pollinations/pollinations/tree/main/.claude/skills/model-debugging
Command: npx skills add https://github.com/pollinations/pollinations --skill model-debugging

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jq, curl, and includes scripts (resource) components.

What problem does it solve?

It helps diagnose model errors across Pollinations services by analyzing logs, identifying patterns, and pinpointing affected users, guiding targeted actions.

Core Features & Use Cases

  • Error Pattern Detection: Analyze logs from Cloudflare Workers, Tinybird, and model endpoints to detect recurring failure modes.
  • Root Cause Guidance: Guide triage focusing on 500/504 backend errors and affected users.
  • Related Skill: See tier-management for user tier actions after issue identification.

Quick Start

Run the model-debugging workflow to identify high-error-rate models and prepare for tier-management actions.

Frequently Asked Questions about model-debugging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug model errors across Pollinations services?▼

Debug model errors by analyzing logs from Cloudflare Workers, Tinybird, and D1 using structured fields like requestId, status, and routePath. Run diagnostic scripts to identify failure patterns, root causes, and affected users across 401, 403, 400, 429, and backend 500/504 errors.

What logs should I analyze when diagnosing model failures?▼

Analyze logs containing requestId, status, body, method, routePath, userAgent, and ipAddress from Cloudflare Workers Observability, D1, and Tinybird. These structured fields reveal request failures, authorization issues, quota events, and backend errors needed for root cause identification.

Can I use this to identify high-error-rate models and affected users?▼

Yes. The workflow detects error patterns across services, pinpoints affected users during authorization and quota events, and guides triage focusing on 500/504 backend errors. Results prepare you for targeted tier-management actions.

What dependencies do I need to run model debugging?▼

You need jq for JSON processing and curl for querying logs. Access to Cloudflare Workers Observability, D1, and Tinybird data sources is required to analyze structured logs and run diagnostic scripts.

Why would I use this instead of manual log inspection?▼

Automated diagnostic scripts process logs efficiently to detect recurring failure modes and patterns across multiple services. This approach scales beyond manual review and systematically identifies root causes guiding targeted remediation.

Related Skills

Explore More Software Engineering Skills→
iterateiterate
198

debug-os-worker

Correlate Cloudflare OS worker observability events to request-level regressions and code locations.

Official
Intermediate
dadbodgeoffdadbodgeoff
783

rate-limiting

Implement subscription-tier aware API rate limiting with sliding window and Redis.

Community
Advanced
itallstartedwithaideaitallstartedwithaidea
31

observability

Implement structured logging, distributed tracing, and error monitoring for Cloudflare Workers.

Community
Advanced
sitharaj88sitharaj88
1

setup-monitoring

Configure application monitoring, logging, error tracking, and alerting with Sentry, Datadog, Grafana, Prometheus, and OpenTelemetry.

Community
Advanced